Clinical decision support for perioperative information management systems

Semin Cardiothorac Vasc Anesth. 2013 Dec;17(4):288-93. doi: 10.1177/1089253213490078. Epub 2013 May 20.


Clinical decision support (CDS) systems are being used to optimize the increasingly complex care that our health care system delivers. These systems have become increasingly important in the delivery of perioperative care for patients undergoing cardiac, thoracic, and vascular procedures. The adoption of perioperative information management systems (PIMS) has allowed these technologies to enter the operating room and support the clinical work flow of anesthesiologists and operational processes. Constructing effective CDS systems necessitates an understanding of operative work flow and technical considerations as well as achieving integration with existing information systems. In this review, we describe published examples of CDS for PIMS, including support for cardiopulmonary bypass separation physiological alarms, β-blocker guideline adherence, enhanced revenue capture for arterial line placement, and detection of hemodynamic monitoring gaps. Although these and other areas are amenable to CDS systems, the challenges of latency and data reliability represent fundamental limitations on the potential application of these tools to specific types of clinical issues. Ultimately, we expect that CDS will remain an important tool in our efforts to optimize the quality of care delivered.

Keywords: cardiac anesthesia; clinical effectiveness quality initiative; high-risk systems; outcome; perioperative information management systems; perioperative system; research.

Publication types

  • Review

MeSH terms

  • Decision Support Systems, Clinical*
  • Delivery of Health Care / methods
  • Delivery of Health Care / standards
  • Guideline Adherence
  • Hospital Information Systems*
  • Humans
  • Medical Informatics / methods
  • Perioperative Care / methods*
  • Perioperative Care / standards
  • Practice Guidelines as Topic
  • Quality of Health Care
  • Reproducibility of Results
  • Workflow