OpenSDE: A strategy for expressive and flexible structured data entry

https://doi.org/10.1016/j.ijmedinf.2005.04.005Get rights and content

Summary

Purpose

: This description focuses on the expressiveness and flexibility of OpenSDE: an application that supports recording of structured narrative data.

Methods

: OpenSDE enables data entry with (customizable) forms based on trees of medical concepts. The relevant scope for data entry can be tailored per medical domain by construction of a domain-specific tree. OpenSDE is intended for structuring narrative data to make these available for both care and research.

Results

: The OpenSDE application is currently in use at several departments in our academic hospital, including radiology, neurology, pediatrics, and child psychiatry. OpenSDE is available for all in open source.

Introduction

Electronic patient data are associated with many potential benefits, e.g. data sharing, decision support, quality assessment, research, and management of patient care [1], [2], [3], [4]. The degree to which patient data are currently available electronically varies. To harvest the potential benefits of electronic data, the data must also be structured to enable processing by computer applications [2]. Structuring the medical narrative poses a significant challenge: content and level of detail are often unpredictable and vary per domain (and even per clinician) [5]. In an attempt to structure medical narratives in a manner that allows for variation and unpredictability, we have developed OpenSDE (SDE: structured data entry). OpenSDE is an application that supports clinicians with the recording of structured data for use in both care and research [6], [7]; data that are till now typically recorded in free text narratives.

Other published work on support of SDE does not provide much insight in the functionality and expressiveness of the respective applications. Therefore, in our description of OpenSDE we focus on those aspects that enable flexibility and expressiveness in data recording. Since OpenSDE is based on the selection of predefined concepts, we also explain why we did not choose to directly adhere to an existing terminology standard. OpenSDE is available in open source [6].

Section snippets

Medical narratives

The medical narrative can be found in diverse sections in the medical record: medical history, family medical history, physical examination, progress notes, and reports (e.g., radiology, surgery, or pathology reports) [8]. Medical narrative data tend to be unruly [5], and only predictable to a certain degree. Free text has been the ideal format to collect these data as it has a high degree of expressiveness [9]. Free text allows clinicians to record data in whatever words, abbreviations, or

OpenSDE: goal and perspective

The goal of OpenSDE is to support structured data entry in a variety of settings, so as to have patient data available for both routine care and retro- and prospective research.1 This

OpenSDE: data entry

The expressiveness provided by the OpenSDE application must not pose (a priori) limits on the level of detail in which one wants to structure data. Not only should data entry be highly expressive, it should also be straightforward. OpenSDE, therefore, applies the following principle for structured data entry. Data can be entered about predefined concepts. These concepts are organized as nodes in a tree structure (we refer to this as a domain model). In this tree, every node is described by its

Discussion

Since OpenSDE domain models are trees of predefined concepts, domain models intuitively resemble a terminology. Therefore, we often receive the question what the difference is between domain models and a terminology, or why we did not use a terminological system instead of our own, manually authored, domain models.

Standardization is essential for the aggregation and pooling of data for clinical research, as well as for the sharing of data between applications that need to process the data [13].

Conclusion

Approaching structured data entry from the care perspective places emphasis on approaching the expressiveness of free text. We chose this perspective because we wanted to ensure that data collection corresponds as much as possible to the needs of the clinicians who are actually recording the data. Having spent effort on enabling data entry in a manner that suits clinicians, the next step is to approach the challenge from the perspective of research. Is it possible to use data that are

Acknowledgements

The authors would like to thank Cobus van Wyk, Georgio Mosis, and Jan Talmon for their helpful comments on previous versions of this manuscript.

The work presented in this paper is funded by a grant from ZonMW.

References (26)

  • A.M. van Ginneken et al.

    A new approach to structured data entry

  • J. van der Lei

    Closing the loop between clinical practice, research, and education: the potential of electronic patient records

    Meth. Inf. Med.

    (2002)
  • A.M. van Ginneken et al.

    Self-contained patient data in ORCA to cope with an evolving vocabulary

    Proc. AMIA Symp.

    (1998)
  • Cited by (32)

    View all citing articles on Scopus
    View full text