BOX 6-2
Rules for Detecting Possible Adverse Drug Events Using Automated Surveillance

Receiving new diphenhydramine AND no diphenhydramine within last 7 days AND patient not on paclitaxel AND no blood transfusion in last 1 day AND no diphenhydramine at bedtime

Receiving oral vancomycin

Blood alkaline phosphatase >350 units/liter (L)

Receiving phytonadione (vitamin K) AND on Coumadin

Receiving ranitidine AND platelet count has fallen to less than 50 percent of previous value or below 100,000

Serum carbamazepine >12.0 micrograms/milliliter (µg/mL)

Serum digoxin >1.7 nanograms (ng)/mL

Serum bilirubin >10 milligrams/deciliter

Serum cyclosporine >500 µg/L

Serum potassium >6.5 millimoles/L

Blood eosinophils >6 percent

Receiving kaopectate

Receiving loperamide

Serum n-acetyl procainamide >20 µg/mL

Serum phenytoin results >20 µg/mL

Serum phenobarbital results >45 µg/mL

Receiving prednisone AND diphenhydramine

Serum procainamide >10 µg/mL

Serum aspartate amino transferase >150 U/L AND no prior result >150 U/L

Serum theophylline >20 µg/mL

Serum valproate >120 µg/mL

Serum quinidine >5 µg/mL

Serum alanine aminotransferase >150 U/L AND no result >150 U/L in last 7 days

SOURCE: Honigman et al., 2001.

this approach is monitoring the progress of individual patients and groups of patients with the same condition as they pass through the care process using measures for assessing the quality of care given, such as those of the Diabetes Quality Improvement Project (DQIP). Another example is monitoring all patients at a particular point in the care continuum, such as through use of a validation system for medical prescribing based on computerized physician order entry. This section examines the general data requirements of these two examples.

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