A distributed system for support and explanation of shared decision-making in the prenatal testing domain

Itay Segal, Yuval Shahar

Research output: Contribution to journalArticlepeer-review

13 Scopus citations


Medical domains involve numerous tests and treatments, the sheer variety of which confounds both care providers and patients. Many of the decisions depend on the patient's preferences. Shared decision-making, which explicitly involves the patients and their preferences, is therefore imperative, but requires also a sufficient explanatory infrastructure. We introduce a distributed application, PANDEX, that, by using decision-analytic methods, assists patients and care providers to reach optimal decisions. Based on a generic architecture, the PANDEX prototype, which focuses on the domain of genetic prenatal consultation, is designed to calculate the optimal treatment strategy based on the patient's clinical data and preferences. A major focus of our study was on developing several types of in-depth sensitivity and importance analysis methods and on the implementation of the respective graphical tools embedded in the system, to help the patient fully understand the recommended strategy. A preliminary assessment of PANDEX by six genetic consultants demonstrated a relative unwillingness to work with PANDEX (mean = 2.16 ± 0.98 (SD), on a scale of 1-5), but a tendency to agree with its recommended strategies (mean = 3.48 ± 1.4) and with its capability to provide insights into the recommended strategies (3.28 ± 1.23). PANDEX was considered by the consultants to be a potentially useful tool for patients.

Original languageEnglish
Pages (from-to)272-286
JournalJournal of Biomedical Informatics
Issue number2
StatePublished - 1 Apr 2009


  • Explanation
  • Influence diagrams
  • Informed consent
  • Medical decision support
  • Medical decision-making
  • Preference elicitation
  • Prenatal diagnosis
  • Sensitivity analysis
  • Shared decision-making

ASJC Scopus subject areas

  • Computer Science Applications
  • Health Informatics


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