Medications requiring dosage adjustments in hepatic disease

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According to JAMIA, “clinical decision support (CDS) provides clinicians, staff, patients, or other individuals with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care.” ( J Am Med Inform Assoc. 2007;14:141–145). CDS has potential to be an efficient and accurate way to identify medications requiring dosage adjustments in hepatic disease.

Although other organ systems are known to metabolize medications, the liver is by far the principal organ responsible for processing and providing major pathways for the biotransformation of many ingested medications. Abnormal function of the liver can result in alterations of drug metabolism. For example, diazepam, a commonly used medication for anxiety, sedation, and muscle spasticity, has a half-life that is doubled in patients with chronic liver failure. [Klotz, U, et al. The effects of age and liver disease on the disposition and elimination of diazepam in adult man. J Clin Invest. 1975;55(2):347–359].

A recently published systematic review of clinical event monitors evaluated the positive predictive value (PPV) for detecting adverse drug events in hospitals. With regard to hepatic function, the authors took studies evaluating elevated or increasing INR, PTT, GGT, bilirubin, transaminases, and alkaline phosphatase. Unfortunately the between study heterogeneity was too high to evaluate the PPV of these tests. (Handler, SM, et al. A Systematic Review of the Performance Characteristics of Clinical Event Monitor Signals Used to Detect Adverse Drug Events in the Hospital Setting. J Am Med Inform Assoc. 2007;14:451– 458).

At Brigham and Women’s Hospital, a study evaluated ADEs via their computer-based system. The alert for hepatotoxic drug use and rising AST or ALT had a PPV of 0.22 and 0.13, respectively. For rapidly increasing INR the PPV was 0.13. For these alerts, the ratio of interventions to number of alerts reviewed in detail (representing likelihood that alert would lead to an intervention) was 0.12, 0.08, and 0.03 for the aforementioned tests. (Sherman, JB, et al. Computer-based system for preventing adverse drug events. Am J Health-Syst Pharm. 2004; 61:1599-603.)

While existing HIS rules have not created outstanding means of identifying real time medications requiring dosage adjustments in hepatic disease, great potential exists. For use in a hospital system, the rules should:

  1. Detect current and potential adverse drug events.
  2. Avoid alert fatigue.
  3. Incorporate future pharmacogenetic data into clinical decision alerts.
  4. Create well defined standards by consensus guidelines for defining rules.
  5. Evaluate sensitivity, specificity, and PPV of rules.

Jennifer LeTourneau 11/13/07