Oncology Data Capture in a Structured Format

Author : johnbright445
Publish Date : 2021-04-15 21:23:13
Oncology Data Capture in a Structured Format

In the context of complex oncology data sets, interoperability refers to the ability to exchange and reuse data across multiple nodes without losing semantic, contextual, or structural information. 1 Reuse of data refers to the use of data for secondary purposes in an external data ecosystem, such as patient care, cancer screening, testing, or clinical trials. Standardizing the arrangement of contextually linked data fields before capturing in an electronic health record (EHR) framework significantly improves interoperability.

Examine the current state of the oncology data ecosystem's Structured Data Capture (SDC) initiative.

Knowledge Produced

SDC is a computer-readable information model that specifies the information content of data-entry types, supports multiple SDC data exchange methods, and allows for secondary use of structured data.

Pertinence

Clinical data can be structured before being entered into computer systems using SDC models. SDC is particularly useful for storing and exchanging rapidly versioned data elements like those used in pathology data sets, cancer staging, and clinical trials.

From the data entry form (DEF) to all downstream clinical records, maintaining structure and context is important for patient care. There are many advantages to centralising data entry field standardisation during the data collection design process, with an emphasis on downstream interoperability and data reuse. 2 Data entry can be made more reliable and effective with the help of centralised expert teams who design data fields and DEF structures. Regardless of EHR manufacturer, organisation, or differences in the cosmetics of DEF and report formats, standardisation of data entry with clear evidence-based data fields helps to ensure full collection of clinically critical data in a familiar format and allows the production of consistent, standardised, and organised reports.

Unfortunately, EHR vendors seldom discuss this form of precapture standardisation. After the data is collected, attempts to standardise and/or merge data fields around EHRs often necessitate a considerable amount of data aggregation and cleaning, and the results are often suboptimal. 6.7 The lack of precapture semantic, contextual, and structural standardisation is thus a major impediment to the complex data analyses needed in oncology investigations, as well as data sharing with patients, their care teams, and other EHR systems. 

The Quality Research and Public Health committee of the standards organisation Integrating the Healthcare Enterprise published Structured Data Capture (SDC) as an open-source technical system (IHE). SDC was created to provide an interoperable solution to the issue of precapture data standardisation. SDC is a model that defines the structure of related data elements (DEs) while maintaining their semantic and contextual integrity. SDC also defines the information content of interoperable DEFs, allowing DEF users to collect, store, and share complex, context-rich data in structured DEs. 9 An SDC template defines the content of a DEF that can be made in a technology-agnostic manner by any EHR provider while retaining an exact representation of the data definitions, allowing the captured data to be shared in an interoperable manner. Complex oncology data sets, such as those used for anatomic pathology, biomarkers, and clinical oncology reporting, can be designed and exchanged using SDC-based DEFs.

SDC has been the distribution format for the College of American Pathologists' electronic Cancer Checklists (eCCs) since 2019. (CAPs). 35 percent to 40 percent of pathologists in North America use these checklists. ten, eleven Most of the information collected on these forms is sent to cancer registries in North America for public health surveillance. 12 and 13 Other clinical specialties, such as radiology and surgery, are looking at using SDC to standardise data entry, provide structured clinical reports, and make downstream data use easier. Another paper in this topic discusses the eCC programme. 

HISTORY OF SDC

The Office of the National Coordinator for Health Information Technology (ONC) launched the SDC project in early 2013 as part of its Standards and Interoperability Framework initiative.

14 The International House of Engineers (IHE) was chosen to host the specification. The IHE SDC Working Group maintains the profile, which is periodically tested at IHE Connectathons. It was first published in October.

The ONC also funded a project to harmonise the FHIR Questionnaire with the IHE SDC17, in order to create a hybrid, functionally comparable FHIR SDC model. However, due to gaps in goals and design concepts, full harmonisation was not achieved, and the two methods diverged. Both the IHE SDC and the FHIR SDC became community-led projects in 2017. This paper focuses solely on IHE SDC.

ARCHITECTURE SDC

SDC is a data model that specifies how different forms of standardised clinical data should be interpreted for technology-independent data collection. SDC's primary data type is DE,18 which includes question-and-answer sets and fill-in questions, but it can also handle traditional media forms including photos in questions and responses. And question and response has its own unique hl7 interface engines  identifier (ID), which remains constant until the question's or answer's contextual semantics shift. SDC sections and DEs can be replicated and nested to any degree of depth to help reflect meaning and monitor the display of shape pieces.

A collection of nested eXtensible Markup Language (XML) schemas describe the structure of SDC. The schemas are used to limit the structure of SDC XML to recurrent patterns and to generate programming code for the SDC Object Model (OM). The OM can be used to monitor the actions of SDC-based DEFs as well as generate SDC XML from SDC modelling software. The SDC Technical Reference Guide contains information on the SDC Schema.

Form Design Files are SDC XML documents (Fig 1) that are used to generate DEFs (FDFs). A variety of techniques can be used to transform an FDF to a DEF. One common method is to turn the FDF into a functional web page using a software (often written in extensible Stylesheet Language with Transformations [XSLT]), with JavaScript controllers to enforce SDC rules and data submission functionality. Most SDC-supporting vendors, on the other hand, do not use webpages to translate the FDF into their chosen software implementation; instead, they use proprietary techniques.

Author Bio: 

This article was written by a Folio3 content researcher. It is a medical production company and a Pharmacy marketing agency headquartered in the United States that serves clients all over the world.



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