HCA 205 Module 7 Diagnostic Tests and Results Example

Positive Does Not Mean Sick: What Diagnostic Test Results Mean for Patients

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Health Care Administration Program, Aspen University

HCA 205: Principles of Health and Disease

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Month Day, Year

Positive Does Not Mean Sick: What Diagnostic Test Results Mean for Patients

Laboratory and imaging tests guide most medical decisions, yet their results are often misunderstood by patients and even by staff. A positive screening test does not always mean disease, and a negative one does not always rule it out. This paper explains how tests are judged, works through the arithmetic of a screening test and follows a composite patient whose stool test came back positive.

Screening and Diagnostic Tests

A screening test checks people who feel well, for instance stool tests for colon cancer or blood sugar tests for diabetes. Diagnostic tests confirm or rule out disease in people with symptoms or a positive screen, for example a colonoscopy booked after an abnormal stool result. Screening tests are designed to be simple and safe, which usually means they are less accurate than diagnostic tests. Knowing which kind of test was done helps staff explain what a result means and what should come next.

Sensitivity and Specificity

Sensitivity is the share of people with a disease whom the test correctly identifies as positive. Specificity is the share of people without the disease whom the test correctly identifies as negative. A highly sensitive test rarely misses disease; a highly specific test rarely raises false alarms. Both are properties of the test itself and stay fixed whether a disease is rare or common in the group tested (Trevethan, 2017).

Predictive Values

Patients ask something else entirely: with this result in hand, what are the odds that I am actually sick? The positive predictive value is the share of positive results that are true positives; the negative predictive value is the share of negative results that are true negatives. Unlike sensitivity and specificity, predictive values depend heavily on how common the disease is in the people tested (Trevethan, 2017). When a disease is rare, even a good test produces more false positives than true positives.

Comparing Two Stool Tests

A large trial compared a multitarget stool DNA test with a fecal immunochemical test in nearly 10,000 people who also had colonoscopy. The DNA test detected 92.3% of cancers compared with 73.8% for the immunochemical test, but its specificity was lower, 86.6% versus 94.9%, among people without advanced findings (Imperiale et al., 2014). The more sensitive test misses fewer cancers but sends more people without cancer to colonoscopy.

A Worked Example

Suppose 1,000 people are screened with a test that has 92% sensitivity and 87% specificity, and 7 of them have colorectal cancer, roughly the 0.7% found in the trial. The table shows the results.

Reading the Example

Of about 135 people with a positive result, only about 6 have cancer, so the positive predictive value is under 5%. Of about 865 with a negative result, about 1 has cancer, so the negative predictive value is above 99.8%. Most positive results are false alarms, which is why every positive screen must be followed by colonoscopy, and why a negative screen is reassuring but still needs repeating at the right interval.

The Composite Patient

Mr. N., a composite 52-year-old mechanic, did a home stool DNA test and received a letter saying it was positive. He called the clinic frightened, convinced he had cancer. The medical assistant explained that most positive results do not mean cancer, but that a colonoscopy was needed to find out and should be scheduled within weeks. His colonoscopy found two small polyps, which were removed; he did not have cancer. His relief afterward showed how much a few clear sentences at the first call could have helped.

Repeat Testing for Diabetes

Some tests are repeated before a diagnosis is made. Under American Diabetes Association standards, a diagnosis of diabetes in a person without clear symptoms requires two abnormal results, either from the same sample using two tests or from two separate samples (American Diabetes Association Professional Practice Committee, 2025). Repeating the test guards against laboratory error and borderline results.

Normal Ranges

Laboratory reports list reference ranges, usually covering the middle 95% of healthy people. That means about 1 in 20 healthy people will have a result outside the range on any single test, and a panel of many tests will often show at least one out-of-range value in a healthy person. A slightly abnormal result must be interpreted with the rest of the clinical picture.

Communicating Results

Staff who communicate results should use plain words, explain what a result means and what happens next, and avoid both false reassurance and alarm. For Mr. N., saying most positive tests do not mean cancer, but we need to check with a colonoscopy, and here is when, would have eased his fear while keeping him on track. Every positive screen needs a tracked follow-up so that no patient is lost between the screen and the diagnostic test.

Tracking Results in the Office

Tests only help if results are seen and acted on. Practices need a system that shows every ordered test until its result is reviewed and the patient is informed. Abnormal results should be flagged, and a staff member should confirm that follow-up, such as a colonoscopy after a positive stool test, has been scheduled and completed. Missed or delayed follow-up of abnormal results is a well-known source of patient harm and legal risk.

Tests That Change Decisions

A useful rule is that a test should be ordered only if its result could change what happens next. Repeating a normal test too often, or ordering a test whose result will not alter treatment, adds cost and the risk of false positives that lead to more testing. Choosing Wisely and similar campaigns encourage clinicians and patients to question tests that add little value, a principle administrators can support through order sets and feedback.

Conclusion

Sensitivity and specificity describe a test, but only predictive values answer the patient's own question about a result, and they depend on how common the disease is. When disease is uncommon, most positive screening results are false alarms and must be confirmed with a diagnostic test. Mr. N.'s experience shows why staff need to understand and explain results, and why follow-up of every positive screen matters.

References

American Diabetes Association Professional Practice Committee. (2025). 2. Diagnosis and classification of diabetes: Standards of care in diabetes-2025. Diabetes Care, 48(Suppl. 1), S27-S49. https://doi.org/10.2337/dc25-S002

Imperiale, T. F., Ransohoff, D. F., Itzkowitz, S. H., Levin, T. R., Lavin, P., Lidgard, G. P., Ahlquist, D. A., & Berger, B. M. (2014). Multitarget stool DNA testing for colorectal-cancer screening. New England Journal of Medicine, 370(14), 1287-1297. https://doi.org/10.1056/NEJMoa1311194

Trevethan, R. (2017). Sensitivity, specificity, and predictive values: Foundations, pliabilities, and pitfalls in research and practice. Frontiers in Public Health, 5, Article 307. https://doi.org/10.3389/fpubh.2017.00307