Determining the cancer diagnostic interval using administrative data in a cohort of patients with pancreatic cancer.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 336-336
Author(s):  
Safiya Karim ◽  
Bailey Paterson ◽  
Shiying Kong ◽  
Alyson Mahar ◽  
Colleen Webber ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Administrative Data ◽  
Control Charts ◽  
Population Based ◽  
Administrative Databases ◽  
Ductal Adenocarcinoma ◽  
Statistical Control ◽  
Presenting Symptoms ◽  
Wide Range ◽  
Diagnostic Interval

336 Background: Pancreatic cancer is a leading cause of cancer death, largely due to vague presenting symptoms and late stage at diagnosis. Population-based administrative data can be a valuable resource for studying the diagnostic interval. The objective of this study was to determine the first encounter in the diagnostic interval and to calculate that interval in a cohort of patients with pancreatic cancer using an empirical approach. Methods: This is a retrospective, cohort study of patients diagnosed with pancreatic ductal adenocarcinoma (PDAC) from 2007 – 2015 in Alberta, Canada. We used the Alberta Cancer Registry (ACR), physician billing claims, hospital discharge and emergency room visits to identify health encounters that occurred more frequently in the 3 months prior to diagnosis compared to those in the 3-24 months prior to diagnosis. We used statistical control charts to define the lookback period for each encounter category and identify the earliest encounter that represented the start of the diagnostic interval (index contact date). The end of the interval was the diagnosis date. Quantile regression was used to determine factors associated with the diagnostic interval. Results: We identified 3142 patients with PDAC. Median age of diagnosis was 71 (IQR 61-80). We identified an index contact date in 96.5% of the patients. The median length of the diagnostic interval was 76 days (IQR 21-191; 90th percentile 276 days). A higher Elixhauser comorbidity score (+18.57 days/ 1 point increase, 95% CI 16.07-21.07, p < 0.001) and stage 3 disease (+22.55 days, 95% CI 5.02-40.08, p = 0.01) was associated with a longer diagnostic interval. Conclusions: In this cohort of patients with pancreatic cancer, there was a wide range in the diagnostic interval with 10% of patients having a diagnostic interval approaching one year. Diagnostic interval research using administrative databases can understand variations in diagnosis times, can inform early detection efforts and can improve quality of care.

Determining the cancer diagnostic interval using administrative data in a cohort of patients with pancreatic ductal adenocarcinoma (PDAC).

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. e13551-e13551
Author(s):  
Bailey Paterson ◽  
Shiying Kong ◽  
Alyson Mahar ◽  
Colleen Webber ◽  
Richard M. Lee-Ying ◽  
...  
Keyword(s):  
Administrative Data ◽  
Control Charts ◽  
Population Based ◽  
Administrative Databases ◽  
Interval Length ◽  
Ductal Adenocarcinoma ◽  
Statistical Control ◽  
Wide Range ◽  
Age Of Diagnosis ◽  
Diagnostic Interval

e13551 Background: PDAC is a leading cause of cancer death that is often diagnosed at an advanced stage. Population-based administrative data can be a valuable resource for studying the diagnostic interval, defined as the time from the first related healthcare encounter to cancer diagnosis. The objective of this study was to determine the diagnostic interval in a cohort of patients with PDAC using an empirical approach. Methods: This is a retrospective, cohort study of patients diagnosed with PDAC from 2007 – 2015 in Alberta, Canada. We used the Alberta Cancer Registry, physician billing claims, hospital discharge and emergency room visits to identify and categorize cancer-related healthcare encounters before diagnosis. We used statistical control charts to define the lookback period for each encounter category and used these lookback periods to identify the earliest encounter that represented the start of the diagnostic interval (index contact date). The end of the interval was the diagnosis date. Quantile regression was used to determine factors associated with the diagnostic interval. Results: We identified 3,142 patients with PDAC. Median age of diagnosis was 71 (IQR 61-80). We identified an index contact date and thus a diagnostic interval in 96.5% of patients. The median diagnostic interval length was 76 days (IQR 21-191; 90th percentile 276 days). A higher Elixhauser comorbidity score (+18.57 days/ 1 point increase, 95% CI 16.07-21.07, p<0.001) and stage 3 disease compared to stage 2 disease (+22.55 days, 95% CI 5.02-40.08, p=0.01) were associated with a longer diagnostic interval. Conclusions: In this cohort of patients with PDAC, there was a wide range in the diagnostic interval with 10% of patients having a diagnostic interval of approximately 9 months. Diagnostic interval research using administrative databases can understand variations in diagnosis times and can inform early detection efforts by identifying where and in whom delays may occur.

scholarly journals Determining the Cancer Diagnostic Interval Using Administrative Health Care Data in a Breast Cancer Cohort

2019 ◽  
pp. 1-10 ◽  
Author(s):  
Patti A. Groome ◽  
Colleen Webber ◽  
Marlo Whitehead ◽  
Rahim Moineddin ◽  
Eva Grunfeld ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Health Care ◽  
Control Charts ◽  
Population Level ◽  
Population Based ◽  
Statistical Control ◽  
Health Care Data ◽  
Cancer Diagnostic ◽  
Breast Cancer Cohort ◽  
Diagnostic Interval

PURPOSE Population-based administrative health care data could be a valuable resource with which to study the cancer diagnostic interval. The objective of the current study was to determine the first encounter in the diagnostic interval and compute that interval in a cohort of patients with breast cancer using an empirical approach. METHODS This is a retrospective cohort study of patients with breast cancer diagnosed in Ontario, Canada, between 2007 and 2015. We used cancer registry, physician claims, hospital discharge, and emergency department visit data to identify and categorize cancer-related encounters that were more common in the three months before diagnosis. We used statistical control charts to define lookback periods for each encounter category. We identified the earliest cancer-related encounter that marked the start of the diagnostic interval. The end of the interval was the cancer diagnosis date. RESULTS The final cohort included 69,717 patients with breast cancer. We identified an initial encounter in 97.8% of patients. Median diagnostic interval was 36 days (interquartile range [IQR], 19 to 71 days). Median interval decreased with increasing stage at diagnosis and varied across initial encounter categories, from 9 days (IQR, 1 to 35 days) for encounters with other cancer as the diagnosis to 231 days (IQR 77 to 311 days) for encounters with cyst aspiration or drainage as the procedure. CONCLUSION Diagnostic interval research can inform early detection guidelines and assess the success of diagnostic assessment programs. Use of administrative data for this purpose is a powerful tool for improving diagnostic processes at the population level.

Epidemiology of pheochromocytoma and paraganglioma: population-based cohort study

2021 ◽  
Vol 184 (1) ◽  
pp. 19-28
Author(s):  
Alexander A Leung ◽  
Janice L Pasieka ◽  
Martin D Hyrcza ◽  
Danièle Pacaud ◽  
Yuan Dong ◽  
...  
Keyword(s):  
Cohort Study ◽  
Administrative Data ◽  
Laboratory Data ◽  
Population Based ◽  
Incidence Rates ◽  
Primary Objective ◽  
Administrative Databases ◽  
Secondary Objective ◽  
True Frequency ◽  
Clinical Records

Objective Despite the significant morbidity and mortality associated with pheochromocytoma and paraganglioma, little is known about their epidemiology. The primary objective was to determine the incidence of pheochromocytoma and paraganglioma in an ethnically diverse population. A secondary objective was to develop and validate algorithms for case detection using laboratory and administrative data. Design Population-based cohort study in Alberta, Canada from 2012 to 2019. Methods Patients with pheochromocytoma or paraganglioma were identified using linked administrative databases and clinical records. Annual incidence rates per 100 000 people were calculated and stratified according to age and sex. Algorithms to identify pheochromocytoma and paraganglioma, based on laboratory and administrative data, were evaluated. Results A total of 239 patients with pheochromocytoma or paraganglioma (collectively with 251 tumors) were identified from a population of 5 196 368 people over a period of 7 years. The overall incidence of pheochromocytoma or paraganglioma was 0.66 cases per 100 000 people per year. The frequency of pheochromocytoma and paraganglioma increased with age and was highest in individuals aged 60–79 years (8.85 and 14.68 cases per 100 000 people per year for males and females, respectively). An algorithm based on laboratory data (metanephrine >two-fold or normetanephrine >three-fold higher than the upper limit of normal) closely approximated the true frequency of pheochromocytoma and paraganglioma with an estimated incidence of 0.54 cases per 100 000 people per year. Conslusion The incidence of pheochromocytoma and paraganglioma in an unselected population of western Canada was unexpectedly higher than rates reported from other areas of the world.

scholarly journals Validation of Carotid Artery Revascularization Coding in Ontario Health Administrative Databases

2016 ◽  
Vol 39 (2) ◽  
pp. 73 ◽  
Author(s):  
Mohamad A Hussain ◽  
Muhammad Mamdani ◽  
Gustavo Saposnik ◽  
Jack V Tu ◽  
David Turkel-Parrella ◽  
...  
Keyword(s):  
Carotid Artery ◽  
Administrative Data ◽  
High Volume ◽  
Population Based ◽  
Administrative Databases ◽  
Ontario Health Insurance Plan ◽  
Stroke Registry ◽  
Administrative Records ◽  
Ischemic Attack ◽  
Procedure Codes

Purpose: The positive predictive value (PPV) of carotid endarterectomy (CEA) and carotid artery stenting (CAS) procedure and post-operative complication coding were assessed in Ontario health administrative databases. Methods: Between 1 April 2002 and 31 March 2014, a random sample of 428 patients were identified using Canadian Classification of Health Intervention (CCI) procedure codes and Ontario Health Insurance Plan (OHIP) billing codes from administrative data. A blinded chart review was conducted at two high-volume vascular centers to assess the level of agreement between the administrative records and the corresponding patients’ hospital charts. PPV was calculated with 95% confidence intervals (CIs) to estimate the validity of CEA and CAS coding, utilizing hospital charts as the gold standard. Sensitivity of CEA and CAS coding were also assessed by linking two independent databases of 540 CEA-treated patients (Ontario Stroke Registry) and 140 CAS-treated patients (single-center CAS database) to administrative records. Results: PPV for CEA ranged from 99% to 100% and sensitivity ranged from 81.5% to 89.6% using CCI and OHIP codes. A CCI code with a PPV of 87% (95% CI, 78.8-92.9) and sensitivity of 92.9% (95% CI, 87.4-96.1) in identifying CAS was also identified. PPV for post-admission complication diagnosis coding was 71.4% (95% CI, 53.7-85.4) for stroke/transient ischemic attack, and 82.4% (95% CI, 56.6-96.2) for myocardial infarction. Conclusions: Our analysis demonstrated that the codes used in administrative databases accurately identify CEA and CAS-treated patients. Researchers can confidently use administrative data to conduct population-based studies of CEA and CAS.

scholarly journals Omics Approaches in Pancreatic Adenocarcinoma

Cancers ◽  
2019 ◽  
Vol 11 (8) ◽  
pp. 1052
Author(s):  
Iranzu González-Boja ◽  
Antonio Viúdez ◽  
Saioa Goñi ◽  
Enrique Santamaria ◽  
Estefania Carrasco-García ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Survival Rate ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Ductal Adenocarcinoma ◽  
Curative Intent ◽  
Pancreatic Cancers ◽  
Wide Range ◽  
Prevention And Treatment ◽  
Shed Light

Pancreatic ductal adenocarcinoma, which represents 80% of pancreatic cancers, is mainly diagnosed when treatment with curative intent is not possible. Consequently, the overall five-year survival rate is extremely dismal—around 5% to 7%. In addition, pancreatic cancer is expected to become the second leading cause of cancer-related death by 2030. Therefore, advances in screening, prevention and treatment are urgently needed. Fortunately, a wide range of approaches could help shed light in this area. Beyond the use of cytological or histological samples focusing in diagnosis, a plethora of new approaches are currently being used for a deeper characterization of pancreatic ductal adenocarcinoma, including genetic, epigenetic, and/or proteo-transcriptomic techniques. Accordingly, the development of new analytical technologies using body fluids (blood, bile, urine, etc.) to analyze tumor derived molecules has become a priority in pancreatic ductal adenocarcinoma due to the hard accessibility to tumor samples. These types of technologies will lead us to improve the outcome of pancreatic ductal adenocarcinoma patients.

scholarly journals Aberrant MicroRNAs in Pancreatic Cancer: Researches and Clinical Implications

2014 ◽  
Vol 2014 ◽  
pp. 1-11 ◽  
Author(s):  
Tao Sun ◽  
Xiangyu Kong ◽  
Yiqi Du ◽  
Zhaoshen Li
Keyword(s):  
Pancreatic Cancer ◽  
Pancreatic Ductal Adenocarcinoma ◽  
Poor Prognosis ◽  
Vital Role ◽  
High Rate ◽  
Ductal Adenocarcinoma ◽  
Clinical Implications ◽  
Circulating Mirnas ◽  
Current Review ◽  
Wide Range

Pancreatic ductal adenocarcinoma (PDAC) is an aggressive malignancy with a high rate of mortality and poor prognosis. Numerous studies have proved that microRNA (miRNA) may play a vital role in a wide range of malignancies, including PDAC, and dysregulated miRNAs, including circulating miRNAs, are associated with PDAC proliferation, invasion, chemosensitivity, and radiosensitivity, as well as prognosis. Greater understanding of the roles of miRNAs in PDAC could provide insights into this disease and identify potential diagnostic markers and therapeutic targets. The current review focuses on recent advances with respect to the roles of miRNAs in PDAC and their practical value.

scholarly journals Prediction of in-hospital mortality after pancreatic resection in pancreatic cancer patients: A boosting approach via a population-based study using health administrative data

PLoS ONE ◽  
2017 ◽  
Vol 12 (6) ◽  
pp. e0178757 ◽  
Author(s):  
Jose F. Velez-Serrano ◽  
Daniel Velez-Serrano ◽  
Valentin Hernandez-Barrera ◽  
Rodrigo Jimenez-Garcia ◽  
Ana Lopez de Andres ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Hospital Mortality ◽  
Cancer Patients ◽  
Administrative Data ◽  
Pancreatic Resection ◽  
Population Based ◽  
Population Based Study ◽  
Health Administrative Data

scholarly journals Validation of endovascular and open thoracoabdominal aortic aneurysm repair in Ontario health administrative databases

2019 ◽  
Vol 42 (2) ◽  
pp. E19-25 ◽  
Author(s):  
Rodolfo V. Rocha ◽  
Mohammed Al-Omran ◽  
Mohamad A. Hussain ◽  
Douglas S. Lee ◽  
Thomas L. Forbes ◽  
...  
Keyword(s):  
Aortic Aneurysm ◽  
Administrative Data ◽  
Thoracoabdominal Aortic Aneurysm ◽  
Population Based ◽  
Administrative Databases ◽  
Ontario Health Insurance Plan ◽  
Administrative Records ◽  
Thoracoabdominal Aortic Aneurysm Repair ◽  
Aneurysm Repair ◽  
Procedure Codes

Purpose: The positive predictive value (PPV) of endovascular and open thoracoabdominal aortic aneurysm (TAAA) repair coding was assessed in Ontario health administrative databases. Methods: Between 1 January 2006 and 31 March 2016, a random sample of 192 patients was identified using Canadian Classification of Health Intervention (CCI) procedure codes and Ontario Health Insurance Plan (OHIP) billing codes from administrative data. Blinded chart reviews were conducted at two cardiovascular centers to assess the level of agreement between the administrative records and the corresponding patients’ hospital charts. The PPV was calculated with 95% confidence intervals using hospital charts as the gold standard. Results: The PPV for the single endovascular TAAA repair code, 1ID80GQNRN, was 0.90 (0.78, 0.97). A combination of all nine CCI open TAAA repair codes was performed, with a PPV of 0.62 (0.47, 0.76). The combination of any one of the nine CCI codes AND the single OHIP code for open TAAA repair (R803) rendered a PPV of 0.98 (0.90, 1.00). Conclusions: Endovascular TAAA repair may be identified using a single CCI code (1ID80GQNRN). Open TAAA repair may be identified using a combination of CCI and OHIP codes. Researchers may therefore use administrative data to conduct population-based studies of endovascular and open repair of TAAA.

Quality indicators for end-of-life breast cancer care: Testing the use of administrative databases

2006 ◽  
Vol 24 (18_suppl) ◽  
pp. 6066-6066 ◽  
Author(s):  
L. Lethbridge ◽  
E. Grunfeld ◽  
R. Dewar ◽  
G. Johnston ◽  
P. McIntyre ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Quality Of Care ◽  
End Of Life ◽  
Administrative Data ◽  
Population Based ◽  
Vital Statistics ◽  
Administrative Databases ◽  
Breast Cancer Patients ◽  
Eol Care

6066 Background: Defining, measuring and monitoring quality of care is a facet of health services research that is growing in importance. Breast cancer offers a disease model to examine quality end-of-life (EOL) care provided to women. Administrative data have the unique potential to provide population-based measures of quality of care. The objective of this study was to assess the feasibility of using routinely-collected administrative data to measure quality EOL care for breast cancer patients. Methods: A cohort of all women in Nova Scotia who died of breast cancer between 01/01/1998 and 31/12/2002 was assembled from the Cancer Registry and Vital Statistics data. The EOL study period was defined as the last 6 months of life. A total of 864 women met the eligibility criteria. After a literature review, an expert panel identified 19 indicators that were potentially measurable through administrative data. Physician billings, hospital discharge abstracts and seniors pharmacare data, supplemented by clinical datasets, were utilized to calculate the statistics with which to represent the indicators. Results: Benchmark measures of care across the cohort show 63.4% died in a hospital, a mean continuity of care index of 0.786, and the mean number of inpatient days in the last 30 was 9.9. Indicators of aggressive care include 9.3% had chemotherapy in the last 14 days, 5.6% had more than 1 emergency room visit in the last 30 days, and 29.1% had more than 14 inpatient days in the last 30 days. Conclusions: Weaknesses of using these data include: 1) fixed variables with an administrative rather than a clinical objective; 2) lack of comprehensiveness of various datasets; and 3) the use of billings data where increasingly physicians are paid through methods other than fee-for-service. Strengths of this approach are: 1) population-based cohort; 2) comprehensiveness of cohort selection through the provincial Vital Statistics file; and 3) accessibility of data. No significant financial relationships to disclose.

The validity of algorithms using health administrative data in identifying cancer-related events in adolescents and young adults: A population-based study using the IMPACT cohort.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18168-e18168
Author(s):  
Jason D Pole ◽  
Paul C. Nathan ◽  
Nancy N. Baxter ◽  
Cindy Lau ◽  
Corinne Daly ◽  
...  
Keyword(s):  
Young Adults ◽  
Administrative Data ◽  
Population Based ◽  
Adolescents And Young Adults ◽  
Administrative Databases ◽  
Time Interval ◽  
Cancer Outcomes ◽  
Health Administrative Data ◽  
Chart Abstraction ◽  
The Impact

e18168 Background: Despite the importance of estimating population level cancer outcomes, most registries do not collect critical events such as relapse and progression. Attempts to use health administrative data to identify these events have focused on older adults and have been mostly unsuccessful. We developed and tested administrative data-based algorithms in a population-based cohort of adolescents and young adults (AYA) with cancer. Methods: We identified all Ontario AYA 15-21 years of age diagnosed with leukemia, lymphoma, sarcoma, or testicular cancer between 1992 and 2012. Chart abstraction was used to determine the end of initial treatment (EOIT) date and subsequent cancer-related events (progression, relapse, second cancer). Linkage to population-based administrative databases identified fee and procedure codes indicating cancer treatment or palliative care. Algorithms that determined EOIT based a time interval free of treatment-associated codes, and new cancer-related events based on billing codes, were compared to chart abstracted data. Results: The cohort comprised 1,404 patients. Time periods free of treatment-associated codes did not validly identify EOIT dates; using subsequent codes to identify new cancer events was thus associated with low sensitivity (56.2%). However, using administrative data codes that occurred after the EOIT date based on chart abstraction, the first cancer-related event was identified with excellent validity (sensitivity 87.0%, specificity 93.3%, PPV 81.5%, negative predictive value 95.5%). Conclusions: While administrative data alone did not validly identify cancer-related events, using administrative data in combination with chart collected EOIT dates was associated with excellent validity. The collection of EOIT dates by cancer registries would significantly expand the potential of administrative data linkage to assess cancer outcomes.

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