SAFER Maternity: A Clinical Decision Support System with an Authoring Tool for Clinicians

Yaelle Chaudy, Thomas Connolly, Brian Magowan, Mario Soflano

Research output: Contribution to conferencePaper

Abstract

Clinical Decision Support (CDS) is a growing field and the technology is increasingly used by both clinicians and patients. In maternity care, numerous guidelines exist on risk assessment and proposed care plans during pregnancy and labour. However, as new evidence arise, these guidelines are subject to change. It is time consuming for clinicians to (i) compile all this information and (ii) keep it up to date. This paper will present our approach to overcome these two issues: the SAFER (Safe Assessment Form to Evaluate Risk) maternity system. This CDS system contains rules extracted from current guidelines on maternity care, they allow care plans to be generated at various stages of gestation based on patient data. The system includes a mobile application and a web interface. The mobile application can be used to visualise care plans and edit patient data, it is available both online and offline with a synchronisation option. The web interface allows clinicians to manage their patients and superclinicians (clinicians with administrator role) to edit the logic used to generate the care plans. That way, the rules can be kept up to date. The system also caters for different sets of rules to be created and used by different health boards since sometimes the guidelines can be interpreted differently.
The SAFER rules were initially created and used in an Excel file format. This paper will present the results of a formative evaluation of the CDS system performed with the clinician who developed the initial Excel file and also tested against the Excel file. The evaluation concluded that the SAFER platform was more robust and that its rules engine was able to represent all the previous rules; based on the decision trees for each care plan rule, 3640 unit tests were generated automatically to make sure that the results provided by the system were the ones expected for all possible combinations of patient data. All the tests were passed successfully. This paper concludes that SAFER maternity is a robust platform that can be used successfully by (i) clinicians to enter patient data and generate reliable care plans, (ii) patients to visualise their care plans and (iii) superclinicians to update the system’s rules.
Original languageEnglish
Number of pages10
Publication statusPublished - 3 Oct 2017
Event2017 Health Informatics Conference - Surgeon's Hall, Edinburgh, United Kingdom
Duration: 3 Oct 20174 Oct 2017

Conference

Conference2017 Health Informatics Conference
CountryUnited Kingdom
CityEdinburgh
Period3/10/174/10/17

Fingerprint

Decision support systems
Decision trees
Risk assessment
Synchronization
Health
Personnel
Engines

Keywords

  • CDSS
  • Pregnancy
  • Maternity
  • Risk Assessment
  • authoring tool

Cite this

Chaudy, Y., Connolly, T., Magowan, B., & Soflano, M. (2017). SAFER Maternity: A Clinical Decision Support System with an Authoring Tool for Clinicians. Paper presented at 2017 Health Informatics Conference, Edinburgh, United Kingdom.
Chaudy, Yaelle ; Connolly, Thomas ; Magowan, Brian ; Soflano, Mario. / SAFER Maternity : A Clinical Decision Support System with an Authoring Tool for Clinicians. Paper presented at 2017 Health Informatics Conference, Edinburgh, United Kingdom.10 p.
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Chaudy, Y, Connolly, T, Magowan, B & Soflano, M 2017, 'SAFER Maternity: A Clinical Decision Support System with an Authoring Tool for Clinicians' Paper presented at 2017 Health Informatics Conference, Edinburgh, United Kingdom, 3/10/17 - 4/10/17, .

SAFER Maternity : A Clinical Decision Support System with an Authoring Tool for Clinicians. / Chaudy, Yaelle; Connolly, Thomas; Magowan, Brian; Soflano, Mario.

2017. Paper presented at 2017 Health Informatics Conference, Edinburgh, United Kingdom.

Research output: Contribution to conferencePaper

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Chaudy Y, Connolly T, Magowan B, Soflano M. SAFER Maternity: A Clinical Decision Support System with an Authoring Tool for Clinicians. 2017. Paper presented at 2017 Health Informatics Conference, Edinburgh, United Kingdom.