Routine data from hospital information systems can support patient recruitment for clinical studies

Clin Trials. 2010 Apr;7(2):183-9. doi: 10.1177/1740774510363013. Epub 2010 Mar 25.

Abstract

Background: Delayed patient recruitment is a common problem in clinical studies. Hospital information systems (HIS) contain data items relevant for inclusion or exclusion criteria of these studies.

Purpose: We developed and assessed a system to support patient recruitment using HIS data.

Methods: We developed a workflow integrated in our HIS to notify study physicians about potential trial subjects. Automatic HIS database queries based on inclusion and exclusion criteria for each clinical study are performed regularly and generate e-mail notifications via a communication server. Study physicians can verify eligibility with a specific HIS study module. The system performance was assessed with a survey addressing utility, usability, stability, change in recruitment rate, and estimated time savings.

Results: During 10 months of operation, 1328 notifications were generated and 329 enrollments (25%) were documented for seven studies. Precision of alerts depends on availability of appropriate HIS items. Utility and usability were assessed as good, and stability as excellent. Users reported an increased patient recruitment rate for three studies. Three studies reported an estimated time saving of 10 min per recruited patient. The main perceived benefit was systematic identification of potentially eligible patients without time-consuming patient screening procedures in the different parts of the hospital.

Limitations: Notifications about potentially eligible patients depend on HIS data quality regarding inclusion/exclusion criteria, in particular, completeness, timeliness, and validity.

Conclusions: Routine HIS data can support patient recruitment for clinical studies by means of an automated notification workflow and efficient access to clinical data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Clinical Trials as Topic / methods*
  • Electronic Mail
  • Hospital Information Systems*
  • Humans
  • Patient Selection*