6.4 Drug Information Practice, Diagnostic Test Accuracy & Pharmacoeconomics
Key Takeaways
A systematic drug information response gathers background, identifies the real question, searches tertiary then secondary then primary sources, and follows up and documents.
Sensitivity is TP/(TP+FN) and specificity is TN/(TN+FP); a negative result on a highly sensitive test rules disease out, and a positive result on a highly specific test rules it in.
Predictive values depend on prevalence: the same test has a much lower positive predictive value in a low-prevalence population.
Cost-minimization assumes equal outcomes, cost-effectiveness uses natural units, cost-utility uses QALYs, and cost-benefit converts outcomes to money.
In Canada, CDA-AMC (formerly CADTH) or INESSS reviews cost-effectiveness, the pCPA negotiates prices, and each public plan makes its own listing decision.
Drug Information Practice, Diagnostic Test Accuracy & Pharmacoeconomics
The Knowledge and Expertise domain (11% of Part I) goes beyond study designs and treatment-effect statistics. Pharmacists must answer drug information requests systematically. They also interpret how well a diagnostic or screening test performs, and understand the economic analyses Canadian payers use to decide coverage. PEBC sample items include definitions such as the cost-benefit analysis and calculations such as odds ratios and number needed to treat.
1. A Systematic Approach to Drug Information Requests
A structured method avoids answering the wrong question. The classic modified systematic approach has seven steps:
- Secure requester demographics: who is asking (patient, physician, nurse), how to reach them, and how urgent it is.
- Obtain background information: the patient's age, weight, renal and hepatic function, diagnoses, current drugs and allergies, and why the question is being asked.
- Determine and categorize the real question: for example, "Can she take this with warfarin?" may really be a question about managing an INR change.
- Develop a search strategy: start with tertiary sources, then secondary, then primary literature.
- Evaluate, analyze and synthesize the evidence for quality and relevance.
- Formulate and communicate the response: a clear recommendation, its rationale and its limitations, in a form suited to the requester.
- Follow up and document: confirm the outcome and keep a record of the question, sources and answer.
| Source tier | What it is | Canadian examples |
|---|---|---|
| Tertiary | Summaries of established knowledge; fast, but can be dated | Compendium of Pharmaceuticals and Specialties (CPS), Compendium of Therapeutic Choices, RxFiles, Canadian product monographs in Health Canada's Drug Product Database (DPD) |
| Secondary | Indexes and abstracting services used to find primary studies | MEDLINE/PubMed, Embase, Cochrane Library |
| Primary | Original research reports | Randomized trials, cohort and case-control studies, case reports |
Other Canadian resources include Canada Vigilance adverse reaction data (searchable through MedEffect), the Drug Shortages Canada database, and Canada's Drug Agency (CDA-AMC), the former CADTH. CDA-AMC publishes reimbursement recommendations and health technology assessments.
2. Diagnostic and Screening Test Accuracy
A 2 × 2 table compares the test result with the true disease state:
| Disease present | Disease absent | |
|---|---|---|
| Test positive | True positive (TP) | False positive (FP) |
| Test negative | False negative (FN) | True negative (TN) |
- Sensitivity = TP ÷ (TP + FN): the proportion of people with the disease who test positive. A highly sensitive test rarely misses disease, so a negative result helps rule it out ("SnNout").
- Specificity = TN ÷ (TN + FP): the proportion of people without the disease who test negative. A highly specific test rarely labels healthy people as diseased, so a positive result helps rule it in ("SpPin").
- Positive predictive value (PPV) = TP ÷ (TP + FP): the chance that a person with a positive result really has the disease.
- Negative predictive value (NPV) = TN ÷ (TN + FN).
- Likelihood ratios: LR+ = sensitivity ÷ (1 − specificity), and LR− = (1 − sensitivity) ÷ specificity. An LR+ above 10 or an LR− below 0.1 shifts probability substantially.
Prevalence matters. Sensitivity and specificity are properties of the test, but PPV and NPV change with how common the disease is in the population tested.
Worked example: a test with 90% sensitivity and 80% specificity is used in 1,000 people with 10% prevalence.
- 100 have the disease: TP = 90, FN = 10.
- 900 do not: TN = 720, FP = 180.
- PPV = 90 ÷ (90 + 180) = 33%. NPV = 720 ÷ 730 = 98.6%.
If the same test is used where prevalence is 50%, the PPV rises to about 82%. This is why screening low-risk populations generates many false positives.
3. Pharmacoeconomic Analyses
All four classic analyses measure costs in money. They differ in how they measure outcomes:
| Analysis | Outcome measure | When it is used | Result expressed as |
|---|---|---|---|
| Cost-minimization (CMA) | Outcomes shown to be equivalent | Choosing between bioequivalent generics or therapeutically equivalent drugs | The cheaper option |
| Cost-effectiveness (CEA) | Natural clinical units (mmHg lowered, events avoided, life-years gained) | Comparing options with the same type of outcome | Cost per unit of effect; incremental cost-effectiveness ratio (ICER) |
| Cost-utility (CUA) | Quality-adjusted life-years (QALYs) | Comparing across diseases; preferred by CDA-AMC | Cost per QALY gained |
| Cost-benefit (CBA) | Outcomes converted to money | Programs with diverse outcomes (for example, a vaccination program) | Net benefit or benefit-to-cost ratio |
- ICER = (Cost_new − Cost_old) ÷ (Effect_new − Effect_old). Example: a new drug costs $12,000 more per patient than standard care and gains 0.4 QALY, so the ICER is $12,000 ÷ 0.4 = $30,000 per QALY.
- Perspective changes what is counted. A public payer perspective counts drug and health-system costs. A societal perspective also counts lost productivity and caregiver time.
- Budget impact analysis estimates total spending for a payer if the drug is listed. It is not a value-for-money analysis.
- Canadian process: after Health Canada approval, CDA-AMC (or INESSS in Quebec) reviews clinical and cost-effectiveness. The pan-Canadian Pharmaceutical Alliance (pCPA) then negotiates prices for public plans, and each plan decides on listing. Canada has no official cost-per-QALY threshold, although figures around $50,000 per QALY are often quoted as a reference point.
Note
A sensitivity analysis tests how robust an economic result is by varying uncertain inputs, such as drug price, efficacy or discount rate. It is unrelated to the sensitivity of a diagnostic test, despite the shared word.
A new rapid test for a bacterial infection has a sensitivity of 90% and a specificity of 80%. It is used in a clinic where 10% of tested patients actually have the infection. Among 1,000 patients tested, what is the positive predictive value of the test?
About 80%
About 99%
About 33%
About 90%
A provincial plan compares a new anticoagulant with warfarin. The analysis expresses outcomes as quality-adjusted life-years gained and reports a result of $30,000 per QALY. Which type of pharmacoeconomic analysis is this?
Cost-utility analysis
Budget impact analysis
Cost-minimization analysis
Cost-benefit analysis
A pharmacist receives a call from a physician: "Is it safe to give my patient clarithromycin?" Following a systematic approach to drug information requests, what should the pharmacist do first?
Answer that clarithromycin is generally safe and well tolerated.
Consult the clarithromycin product monograph and read the warnings section aloud.
Search MEDLINE for randomized trials of clarithromycin safety before speaking further with the physician.
Gather background information, such as the indication, current medications, renal function and allergies.
Sections you finish are checked off in the contents.