Systematic extraction of diagnostic data items for common high-risk pregnancies using Delphi technique

The quality of clinical decisions made by on-call physician is totally dependent on the quality of medical information received from resident. Some factors such as type, number, format, quality and also the volume of such information may highly affect the quality of remote consultations. Therefore, developing a trusted standard model for such clinical communication seems to be necessary. This study was conducted with aim to design a clinical archetype (structure data) for remote decision making in high-risk pregnancies.
This multi-stage cross-sectional study was conducted by using Delphi technique for identifying of the most common high-risk pregnancies to design a archetype for clinical decision making in three obstetrics and gynecology departments of educational hospitals, Mashhad.
There were 5 common high-risk pregnancies (leading to delivery) including hypertension, third trimester hemorrhage, PROM, pre-term and post-term delivery. 161 clinically-important groups / items were extracted from scientific references and then hand-filtered to 158 items by the participating gynecology and obstetrics experts. The final items were categorized into five classes including general information, chief complaint / current problem, medical history, clinical examination, and paraclinic results.
Our findings showed that close interaction between clinicians and specialists in medical informatics may facilitate the improvement process of medical teleconsultations.