Integration of a cancer registry dataset into a hospital-wide central data warehouse.

212 Background: The ability to link cancer registry data to clinical and administrative data sets for quality improvement has long been desired. We sought to integrate registry data into a central data warehouse in an effort to make available for the first time consistent and reliable diagnosis and staging data to a broad hospital user group. Methods: After a short period of data analysis, the tables for Cancer Registry data (Oracle) were modeled. The source data (SQL Server) was conformed and integrated using an ETL tool (Informatica). All ETL QA work was performed with SQL queries. Cancer registry data was integrated into reporting architecture (Microstrategy) to facilitate design of standardized and ad hoc reports. Results: 140 distinct fields on demographics, staging (clinical, pathological, collaborative), site specific categories, diagnosis, and treatment were integrated into the Dana-Farber Analytics Reporting Tool (DART) for historic Cancer Registry data beginning with January 2010 newly diagnosed cancers. All Cancer Registry data and patient files (new and old) are updated in DART on a monthly basis. Conclusions: Individuals across the hospital now have the ability to link clinical and administrative data from our EMR, institutional QI data from varied systems, and pharmacy data to Cancer Registry data in the DART tool. One example of the integration of these multiple data sets is the linkage of staging data from the Cancer Registry data set and time to referral data from the administrative data set by patient MRN. As DFCI aims to cohort its patients based on their primary diagnosis for quality improvement and other internal reporting needs, the ability to analyze patients in this way becomes critical. This project sets an example for other centers as they integrate Cancer Registry data into user friendly business intelligence systems to help meet federal reporting mandates and aid internal improvement work. [Table: see text]

Download Full-text

A national quality improvement effort: Cancer registry data

Journal of Surgical Oncology ◽

10.1002/jso.2930580304 ◽

1995 ◽

Vol 58 (3) ◽

pp. 155-161 ◽

Cited By ~ 27

Author(s):

Lucy Kamell ◽

Suzanna S. Hoyler ◽

Jennifer E. Seiffert ◽

John L. Young ◽

Donald E. Henson ◽

...

Keyword(s):

Quality Improvement ◽

Cancer Registry ◽

Registry Data ◽

Quality Improvement Effort ◽

Cancer Registry Data ◽

National Quality ◽

Improvement Effort

Download Full-text

P5-14-12: Bayesian Belief Network Mortality Analysis of a Breast Cancer Registry Data Set.

10.1158/0008-5472.sabcs11-p5-14-12 ◽

2011 ◽

Author(s):

JS Eberhardt ◽

T Hyslop ◽

E Mitchell ◽

H Hu ◽

H Rui

Keyword(s):

Breast Cancer ◽

Cancer Registry ◽

Bayesian Belief Network ◽

Registry Data ◽

Data Set ◽

Belief Network ◽

Cancer Registry Data ◽

Breast Cancer Registry ◽

Mortality Analysis

Download Full-text

Information Management in Cancer Registries: Evaluating the Needs for Cancer Data Collection and Cancer Research

Online Journal of Public Health Informatics ◽

10.5210/ojphi.v7i2.5664 ◽

2015 ◽

Vol 7 (2) ◽

Cited By ~ 2

Author(s):

Iris Zachary ◽

Suzanne A Boren ◽

Eduardo Simoes ◽

Jeannette Jackson-Thompson ◽

J. Wade Davis ◽

...

Keyword(s):

Public Health ◽

Data Collection ◽

Cancer Registry ◽

Cancer Registries ◽

Registry Data ◽

Data Set ◽

Common Data Elements ◽

Cancer Registry Data ◽

Treatment Data ◽

Data Elements

Cancer registry data collection involves, at a minimum, collecting data on demographics, tumor characteristics, and treatment. A common, identified, and standardized set of data elements is needed to share data quickly and efficiently with consumers of this data. This project highlights the fact that, there is a need to develop common data elements; Surveys were developed for central cancer registries (CCRs) and cancer researchers (CRs) at NCI-designated Cancer Centers, in order to understand data needs. Survey questions were developed based on the project focus, an evaluation of the research registries and database responses, and systematic review of the literature. Questions covered the following topics: 1) Research, 2) Data collection, 3) Database/ repository, 4) Use of data, 5) Additional data items, 6) Data requests, 7) New data fields, and 8) Cancer registry data set. A review of the surveys indicates that all cancer registries’ data are used for public health surveillance, and 96% of the registries indicate the data are also used for research. Data are available online in interactive tables from over 50% of CRs and 87% of CCRs. Some other survey responses indicate that CCR treatment data are not complete for example treatment data, however cancer researchers are interested in treatment variables from CCRs. Cancer registries have many data available for review, but need to examine what data are needed and used by different entities. Cancer Registries can further enhance usage through collaborations and partnerships to connect common interests in the data by making registries visible and accessible.Keywords: Public Health; Disease Registries; Disease Reporting

Download Full-text

Incidence Patterns and Survival of Gynecological Sarcoma in Germany: Analysis of Population-Based Cancer Registry Data on 1066 Women

International Journal of Gynecological Cancer ◽

10.1097/igc.0000000000001128 ◽

2018 ◽

Vol 28 (1) ◽

pp. 134-138 ◽

Cited By ~ 9

Author(s):

Klaus Pietzner ◽

Nina Buttmann-Schweiger ◽

Jalid Sehouli ◽

Klaus Kraywinkel

Keyword(s):

Cancer Registry ◽

Survival Rates ◽

Female Genital Tract ◽

Relative Survival ◽

Endometrial Stromal Sarcoma ◽

Population Based ◽

Registry Data ◽

Uterine Leiomyosarcoma ◽

Data Set ◽

Cancer Registry Data

ObjectiveSarcomas of the female genital tract are rare tumors. They are described to be associated with a poor prognosis when compared with gynecogical carcinoma. The aim of this study was to report incidence patterns and survival rates for gynecological sarcoma (GS) in Germany.Methods/MaterialsClinical data and survival rates for patients with GS diagnosed in Germany between 2009 and 2013 were extracted from the German national center for population-based cancer registry data. Incidence patterns and 5-year relative survival rates were calculated.ResultsA total of 1066 GSs were included in our analysis during a 5-year time span. The uterus was the most common site, with 87.9% of all cases. The annual age-standardized incidence rate (old European standard) was 8.7 per 1 million women for all GSs. The median age at diagnosis was 59 years. The prognosis ranged according to site, stage, and subtype, for example, from a 5-year relative survival of 53.0% (uterine leiomyosarcoma) if confined to the pelvis, to a very good 5-year relative survival of 97.2% (endometrial stromal sarcoma).ConclusionsDespite the rareness of GS, the size of the data set allows for a differentiation of subtypes according to morphology and site of origin. Clinically relevant differences in incidence and prognosis between subgroups were observed.

Download Full-text

Dotting the “i” of Interoperability in FAIR Cancer-Registry Data Sets

10.5772/intechopen.101330 ◽

2021 ◽

Author(s):

Nicholas Nicholson ◽

Francesco Giusti ◽

Luciana Neamtiu ◽

Giorgia Randi ◽

Tadeusz Dyba ◽

...

Keyword(s):

Cancer Registry ◽

Description Logic ◽

Description Logics ◽

Population Based ◽

Domain Model ◽

Registry Data ◽

Data Sets ◽

Cancer Registry Data ◽

Fair Principles ◽

Quality Dimensions

To conform to FAIR principles, data should be findable, accessible, interoperable, and reusable. Whereas tools exist for making data findable and accessible, interoperability is not straightforward and can limit data reusability. Most interoperability-based solutions address semantic description and metadata linkage, but these alone are not sufficient for the requirements of inter-comparison of population-based cancer data, where strict adherence to data-rules is of paramount importance. Ontologies, and more importantly their formalism in description logics, can play a key role in the automation of data-harmonization processes predominantly via the formalization of the data validation rules within the data-domain model. This in turn leads to a potential quality metric allowing users or agents to determine the limitations in the interpretation and comparability of the data. An approach is described for cancer-registry data with practical examples of how the validation rules can be modeled with description logic. Conformance of data to the rules can be quantified to provide metrics for several quality dimensions. Integrating these with metrics derived for other quality dimensions using tools such as data-shape languages and data-completion tests builds up a data-quality context to serve as an additional component in the FAIR digital object to support interoperability in the wider sense.

Download Full-text

DataLink Record Linkage Software Applied to the Cancer Registry of Murcia, Spain

Methods of Information in Medicine ◽

10.3414/me0529 ◽

2008 ◽

Vol 47 (05) ◽

pp. 448-453 ◽

Cited By ~ 3

Author(s):

M. D. Chirlaque ◽

C. Navarro ◽

M. Márquez Cid

Keyword(s):

Cancer Registry ◽

Record Linkage ◽

Computing Time ◽

Probabilistic Methods ◽

Computational Time ◽

Data Sets ◽

Data Set ◽

Clustering Techniques ◽

Cancer Registry Data ◽

Language Data

Summary Objectives: Record linkage between data sets is relatively simple when unique, universal, permanent, and common variables exist in each data set. This situation occurs infrequently; thus, there is a need to apply probabilistic methods to identify corresponding records. DataLink has been tested to determine if the use of clustering techniques will improve performance with a minimum decrease in accuracy. Methods: The study uses cancer registry data which includes hospital discharge and pathology reports from two hospitals in the Murcia Region for the years 2002-2003. These data are standardized prior to running DataLink. The original version of DataLink compares all of the records one by one, and in two later versions of the software clustering is applied which filters for one or more variables. Computing time and the proportion of detected matches have been investigated with each version. Results: The clustering versions achieve 96.1% and 96.2% accuracy, respectively. An improvement in the computational time of 97.3% and 98.6% is achieved for the two clustering versions compared with the original. The clustering versions lose 0.36% and 1.07% of real duplicates, respectively. Conclusions: DataLink implements deterministic and probabilistic record linkage to eliminate duplicates and to merge new information with existing cases. The standardization of variables to a common format has been adapted to the characteristics of Spanish language data. Clustering techniques minimize computational time and maximize accuracy in the detection of corresponding records.

Download Full-text

Treatable but not curable cancer in England: a retrospective cohort study using cancer registry data and linked data sets

BMJ Open ◽

10.1136/bmjopen-2020-040808 ◽

2021 ◽

Vol 11 (1) ◽

pp. e040808

Author(s):

Rachel White ◽

Fintan Stanley ◽

Jen Than ◽

Archie Macnair ◽

Joanna Pethick ◽

...

Keyword(s):

Cohort Study ◽

Cancer Registry ◽

Retrospective Cohort Study ◽

Retrospective Cohort ◽

Linked Data ◽

Large Population ◽

Registry Data ◽

Data Sets ◽

Cancer Registry Data ◽

Personalised Treatment

ObjectivesThis study estimates the prevalence of cancers that are categorised as treatable but not curable (TbnC) in England. It provides a quantification of the population and a framework to aid identification of this group to enable the design of tailored support services.DesignThrough consultation with clinical and data experts an algorithmic definition of TbnC was developed. Using cancer registry data sets, with five other linked data sets held by the National Disease Registration Service, the algorithm was applied as part of this retrospective cohort study to estimate the size and characteristics of the TbnC population.Setting and participantsThe health data records of 1.6 million people living with cancer in England in 2015, following a cancer diagnosis between 2001 and 2015, were retrospectively assessed for TbnC status.ResultsAn estimated 110 615 people in England were living with TbnC cancer at the end of 2015, following identification of TbnC cancer between 2012 and 2015. In addition, 51 946 people fit the initial search criteria but were found to have been in their last year of life at the end of 2015 and therefore considered separately here as end of life cases. A further 57 117 people in England were initially identified as being at high risk of recurrence or having their life being shortened by cancer but did not fit the TbnC conceptual framework and were excluded, but their results are also reported under ‘group B’.ConclusionsA population living with TbnC cancer can be identified using data currently collected on a national scale in England. This large population living with TbnC cancer requires personalised treatment and support.

Download Full-text

German oncology certification system for colorectal cancer – relative survival rates of a single certified centre vs. national and international registry data

Innovative Surgical Sciences ◽

10.1515/iss-2021-0002 ◽

2021 ◽

Vol 0 (0) ◽

Author(s):

Maximilian Richter ◽

Lena Sonnow ◽

Amir Mehdizadeh-Shrifi ◽

Axel Richter ◽

Rainer Koch ◽

...

Keyword(s):

Colorectal Cancer ◽

Rectal Cancer ◽

International Comparison ◽

Cancer Registry ◽

Survival Data ◽

Survival Rates ◽

Relative Survival ◽

Registry Data ◽

Cancer Registry Data ◽

Colon And Rectal Cancer

Abstract Objectives To evaluate how the certification of specialised Oncology Centres in Germany affects the relative survival of patients with colorectal cancer (CRC) by means of national and international comparison. Methods Between 2007 and 2013, 675 patients with colorectal cancer, treated at the Hildesheim Hospital, an academic teaching hospital of the Hannover Medical School (MHH), were included. A follow-up of the entire patient group was performed until 2014. To obtain international data, a SEER-database search was done. The relative survival of 148,957 patients was compared to our data after 12, 36 and 60 months. For national survival data, we compared our rates with 41,988 patients of the Munich Cancer Registry (MCR). Results Relative survival at our institution tends to be higher in advanced tumour stages compared to national and international cancer registry data. Nationally we found only little variation in survival rates for low stages CRC (UICC I and II), colon, and rectal cancer. There were notable variations regarding relative survival rates for advanced CRC tumour stages (UICC IV). These variations were even more distinct for rectal cancer after 12, 36 and 60 months (Hildesheim Hospital: 89.9, 40.3, 30.1%; Munich Cancer Registry (MCR): 65.4, 28.7, 16.6%). The international comparison of CRC showed significantly higher relative survival rates for patients with advanced tumour stages after 12 months at our institution (77 vs. 54.9% for UICC IV; raw p<0.001). Conclusions Our findings suggest that patients with advanced tumour stages of CRC and especially rectal cancer benefit most from a multidisciplinary and guidelines-oriented treatment at Certified Oncology Centres. For a better evaluation of cancer treatment and improved national and international comparison, the creation of a centralised national cancer registry is necessary.

Download Full-text