How to apply:
Complete the student application

Location:
Iowa City or Ankeny, Iowa

Description:
The candidate will be evaluating raw screening data from computer databases and INMSP partners to calculate the following “Performance Metrics” for the disorders reported by the Newborn Screening Laboratory:

1. Positive Predictive Value (PPV)
1. The positive predictive value of a test is the probability that the patient has the disease when restricted to those patients who test positive.
2. PPV = (Total CP/CP+FP) ● 100 = %
3. CP = confirmed positives; FP = false positives
2. Detection Rate (DR)
1. The detection rate of a newborn screening program is expressed as the number of neonates that on average needs to be tested to detect one affected patient. This is often referred to as the “Prevalence”.
2. A more truthful detection rate should use combined data from four to five years of screening.
3. DR = Volume/CP = 1:??
3. Specificity
1. Specificity is the ability of a test to correctly exclude individuals who do not have a given disease or disorder.
2. The more specific a test, the fewer “false-positive” results it produces.
3. The goal is to have a specificity of at least 95% or greater.
4. Specificity = (TN/FP+TN) ● 100 = xx.xx%
5. True Negatives= TN
4. False Positive Rate (FPR)
1. The false positive rate of a newborn screening program is expressed as the proportion of positive tests in patients proven by follow up evaluation not to have one of the conditions targeted by the newborn screening program.
2. The FPR target is less than 0.3%.
3. FPR = (FP/Volume) ●100 = x.xx%
4. Volume = population
5. Sensitivity
1. Sensitivity is the ability of a test to identify individuals who have a given disease or disorder.
2. The more sensitive a test, the fewer “false-negative” results it produces.
3. Although the goal has historically been to achieve 100% sensitivity, even at the expense of specificity if necessary, it may not be applicable for some of the metabolic disorders that are not reliably detectable in the immediate newborn period.
4. Sensitivity = (CP/CP+FN) ● 100 = (hopefully) 100 %
6. Negative Predictive Value (NPV)
1. The negative predictive value of a test is the probability that the patient is truly negative when restricted to those patients who test negative.
2. The ideal negative predictive value is 100%.
3. NPV = (TN/FN+TN) ● 100 = 100%
4. FN = false negative
7. Method Detection Limit summary
8. Reporting Limit or Quantitation Limits
9. Accuracy
10. Precision
11. Holding Time
12. Turn-around time

Desired Skills:
The student will have received training in the following areas:

1. Systems Analysis
2. Basic (and hopefully some advanced) training in computer use:
1. Microsoft Word
2. Excel
3. Database queries
4. Standard Query Language (SQL)
3. Statistics course work.
4. Epidemiology course work.
5. Laboratory experience is a plus, but not necessary.

Start/End Dates if specific: TBD with student input

Ongoing/variable/negotiable dates: Yes

Average number of hours/week expected: TBD with student input (200 hours total)

Must all work take place on-site? No

Is tele-commuting possible for part of the work commitment? Yes