Sensitivity Calculation

• 1). Determine the true positives; that is, the patient has the disease and the test is positive. Determine the false negatives; the patient has the disease, but the test is negative.
  
  
• 2). Add the true positives and false negatives together. Divide the true positives by this result.
  
  
• 3). Describe the value as a percentage. A result of 75 percent predicts that 75 percent with a positive test have the disease, while 25 percent with a negative test result will also have the disease, and the test has misdiagnosed them.
  
  

Specificity Calculation

• 1). Determine the true negatives: The patient does not have the disease and the test result was correctly negative. Determine the false positives: The patient has a positive test but does not have the disease.
  
  
• 2). Add the true negatives and false positives together. Divide the true positives with this result to give the specificity of the test.
  
  
• 3). Describe the answer as a percentage; a value of 75 percent correctly determines that 75 percent of patients with a negative result do not have the disease, while 25 percent of patients with a negative result actually have the disease.