Clinical decision support systems for addressing information needs of physicians

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This article reviews research regarding the CDSS and its effectiveness. Also, briefly presents system like alert, critique and reminders. Further, explores research related to computerized clinical practice guidelines and expert systems.

Problems of information encountered by physicians

For every 1 to 2 patients seen, the physicians’ have at least one unanswered question [1]. This was the same for physicians from both primary and specialty care, and also from urban and rural areas. The questions were found to be concerning medical opinion, fact and non-medical information about the patient. This missing information contributes to adverse events in health care for the patient. Moreover, with ever increasing medical information, according to an estimate a physician today needs 2 million pieces of information to practice medicine.

Clinical decision support systems

A CDSS generates case specific advice by using patient data and medical knowledge. By coupling it with EMR and CPOE, it presents significant information to physician at time of decision making.

Alert, critique, and reminder CDSS

  • Alerting system: It presents alerts based on alerting criteria by continuously comparing patient data against predetermined criteria. In 2 studies it was found that alerting system was able to positively affect the way physician monitor their patients.
  • Critiquing system: It gets activated when physician enters a medical order, and presents evidence based critique regarding the order entered.
  • Reminder system: Reminds clinicians to follow guidelines. This system was found especially effective in preventive services.

Computer-interpretable clinical practice guidelines

Clinical guidelines have been developed to standardize care and evidence based practice. The struggle faced is the level of compliance to these guidelines by clinicians. The other difficulty faced is is making these narrative guidelines computer interpretable guidelines (CIG).

Expert systems

It is supposed to provide expert quality advice using the knowledge derived from human experts and hard scientific data, using the artificial intelligence program. Systems like de-Dmombal, Mycin, Quick medical reference (QMR), DXplain and Isabel, represent efforts to create expert systems that can aid diagnosis.

Effectiveness of CDSS

Mixed results have been observed. Some studies have shown unsatisfactory results, especially when CDSS is compared to expert physicians. Other studies have shown improved physician performance and clinical practices but CDSS effects on patient outcomes remain questionable.


Patient care is negatively affected by physicians having to practice with incomplete information. CDSS is looked upon to aid this information gap. CDSS is slowly being adapted as a tool to aid physicians rather than becoming their replacements.


This article address a very curtail issue about the health care that is lack of complete information about the patient and medical information in general. CDSS seems to able to provide solution to this issues but it has its own obstacles like conversion of input of data, conversion of clinical guidelines to computer interpretable guidelines and physicians acceptance of CDSS as an aid to their practice.


  1. Denekamp, Y. (2007). Clinical decision support systems for addressing information needs of physicians. The Israel Medical Association journal: IMAJ,9(11), 771-776.