Structured Data Capture for Oncology

Abstract

Lack of interoperability is one of the greatest challenges facing healthcare informatics. Recent interoperability efforts have focused primarily on data transmission and generally ignore data capture standardization. Structured Data Capture (SDC) is an open-source technical framework that enables the capture and exchange of standardized and structured data in interoperable data entry forms (DEFs) at the point of care. Some of SDC's primary use cases concern complex oncology data such as anatomic pathology, biomarkers, and clinical oncology data collection and reporting. Its interoperability goals are the preservation of semantic, contextual, and structural integrity of the captured data throughout the data's lifespan. SDC documents are written in eXtensible Markup Language (XML) and are therefore computer readable, yet technology agnostic-SDC can be implemented by any EHR vendor or registry. Any SDC-capable system can render an SDC XML file into a DEF, receive and parse an SDC transmission, and regenerate the original SDC form as a DEF or synoptic report with the response data intact. SDC is therefore able to facilitate interoperable data capture and exchange for patient care, clinical trials, cancer surveillance and public health needs, clinical research, and computable care guidelines. The usability of SDC-captured oncology data is enhanced when the SDC data elements are mapped to standard terminologies. For example, an SDC map to Systematized Nomenclature of Medicine Clinical Terms (SNOMED CT) enables aggregation of SDC data with other related data sets and permits advanced queries and groupings on the basis of SNOMED CT concept attributes and description logic. SDC supports terminology maps using separate map files or as terminology codes embedded in an SDC document.

FIG 1.

SDC data element. The figure shows an example of an SDC XML data element corresponding to a multiselect question, with the matching part of an eXtensible Stylesheet Language with Transformation-generated HTML DEF shown in the inset (lower right). Each of the 3 answer choices in the DEF inset matches to a ListItem in SDC XML. ListItem elements are nested under the Question element with wrapper elements in the sequence Question → ListField → List→ {ListItems}, where {ListItems} represents the list of ListItem elements. As shown in the Histologic Type DEF (inset), a user has selected the first and third answer choices. In the SDC XML, a selected answer choice is expressed with the selected = “true” expression on the corresponding ListItem elements. The expression maxSelections = “0” on the ListField element indicates that the Question is multiselect. Note that each Question and ListItem has a unique ID attribute. The .100004300 part of each ID is the namespace designation for the College of American Pathologists. DEF, data entry form; ID, identifier; SDC, Structured Data Capture; XML, eXtensible Markup language; XSLT, eXtensible Stylesheet Language with Transformations. (From NAACCR Volume V, with slight modification. Used with permission from NAACCR.)

FIG 2.

SNOMED CT modeling designed for use with SDC and common data element–based data analysis. The figure shows the SNOMED CT concept for Histologic type of primary malignant neoplasm of colon. The right portion of the figure shows the concept’s stated definition (ie, the definition provided by the concept author), which indicates that it is an observation of the histology type of a primary malignant neoplasm located in the colon made at a single point in time. The left portion of the figure, inside the grey rectangle, represents the classified concept definition (ie, the augmented definition produced from the SNOMED CT description logic classifier), which asserts that the observation is a subtype of observation of histology of primary malignant neoplasm and several other higher-level concepts. Furthermore, the concept is grouped, or aggregated, with all other types of observations of histologic types of primary malignancies regardless of organ, such as prostate and melanoma. This classified definition supports data queries such as “find any instance of adenocarcinoma in any organ” or “find all histologic types associated with primary colon tumors.” SDC, Structured Data Capture; SNOMED CT, Systematized Nomenclature of Medicine Clinical Terms.

FIG 3.

SDC on FHIR. The figure shows submission of several SDC forms with SDC on FHIR, using FHIR DocumentReference and Observation in a Bundle. Arrow 1 shows a group of SDC forms being processed for inclusion in an FHIR bundle. Arrow 2 shows the use of SDC on FHIR to submit the FHIR bundle from a sending server to a receiving server. Arrow 3 shows submission of the SDC on FHIR bundle to a receiver. Arrow 4 shows submission to a database end point. Arrow 5 shows the extraction, transformation, and transfer of that data to permit viewing by end users. SDC, Structured Data Capture.