Situation: The nurse at a Rural Health Unit (RHU) joins a team evaluating a point-of-care hemoglobin test for anemia in pregnant women. The laboratory hemoglobin test is the reference standard. The RHU is considering a second device with a sensitivity of 90% and a specificity of 80% to screen 1,000 adolescent girls, among whom the prevalence of anemia is 10%. Assuming sensitivity and specificity stay the same in this group, what positive predictive value (PPV) should the nurse expect? Round off to one decimal place.

With 10% prevalence, 100 girls have anemia and 900 do not. True positives = 0.90 × 100 = 90; true negatives = 0.80 × 900 = 720, so false positives = 900 − 720 = 180. PPV = 90 ÷ (90 + 180) × 100 = 90 ÷ 270 × 100 = 33.3%. Because PPV depends on prevalence, a good test gives many false positives when the condition is uncommon.

This question asks you to calculate the positive predictive value (PPV) of a screening test when the prevalence of the target condition is known. The PPV is the probability that a person with a positive test result actually has the disease. Unlike sensitivity and specificity, which describe the test itself, PPV changes with the population being screened.

Here, the prevalence of anemia is 10%. In a group of 1,000 adolescent girls, that means 100 girls truly have anemia and 900 do not. The device has a sensitivity of 90%, so it correctly identifies 90 of the 100 anemic girls as positive (true positives). The specificity is 80%, meaning it correctly identifies 720 of the 900 non-anemic girls as negative (true negatives). The remaining 180 non-anemic girls are incorrectly labeled positive (false positives).

PPV is calculated as true positives divided by all positive results. Therefore, PPV = 90 ÷ (90 + 180) × 100 = 33.3%. Even with a sensitivity of 90%, only about one-third of positive results represent true anemia when the prevalence is low.

Key point! The large number of false positives arises because the specificity of 80% is applied to a very large group of healthy girls. When a condition is uncommon, even a small false-positive rate produces many false-positive results, diluting the PPV.

Point-of-care (POC) hemoglobin devices are attractive in rural or resource-limited settings because they provide rapid results without a full laboratory. The study by Sobhy et al. ^[1] reviewed the accuracy of on-site tests for anemia during prenatal care and noted that access to laboratory facilities is limited in low- and middle-income countries, making on-site testing a practical option. However, the clinical value of such screening depends not only on how well the device measures hemoglobin but also on how the test result is interpreted in a specific population.

Ssuuna et al. evaluated four POC hemoglobin devices used in routine HIV and maternity care in Uganda against a laboratory gold standard. Their work highlights that multiple factors can affect POC device performance in real-world settings. This reinforces the idea that a device with fixed sensitivity and specificity will produce different predictive values depending on the prevalence of anemia in the group being screened. In a high-prevalence antenatal clinic, a positive POC result is more likely to be a true positive than in a low-prevalence adolescent screening program.

Jegadeesan et al. compared clinical pallor at different anatomical sites for detecting anemia in pregnant women, using a portable hemoglobin device as the reference standard. Their study illustrates a broader point: in primary care, clinicians often rely on simple, low-cost screening methods, but the interpretation of any screening result must account for the underlying prevalence of anemia in that setting.

Term	Definition	Depends on prevalence?
Sensitivity	Proportion of truly anemic individuals who test positive	No
Specificity	Proportion of truly non-anemic individuals who test negative	No
PPV	Proportion of positive results that are true positives	Yes
NPV	Proportion of negative results that are true negatives	Yes

Watch out! A common error is to assume that a test with high sensitivity will have a high PPV. That is only true when the prevalence is high. In this scenario, the prevalence of 10% is low enough that the PPV falls to 33.3% despite the 90% sensitivity.

When interpreting a positive POC hemoglobin result in a low-prevalence population, the nurse should recognize that many positive results will be false positives. This has practical implications: a positive screening result in an adolescent girl with a low pretest probability of anemia should be confirmed with a laboratory hemoglobin measurement before initiating treatment or referral.

The calculation also demonstrates why screening programs must consider the target population. Screening 1,000 adolescent girls with a 10% anemia prevalence will generate 270 positive results, but only 90 of those girls truly have anemia. The remaining 180 would undergo unnecessary follow-up testing or potentially receive iron supplementation they do not need.