Disease-State Insights for Pre-Launch Planning
How to build disease-state insights before launch: epidemiology, patient journey, diagnosis gaps, treatment patterns, and the HCP landscape.
The short answer
Disease-state insights describe how a condition is experienced, diagnosed, and treated today: how many patients there are, where they get stuck, which HCPs see them, what treatments they use, and why. Built before launch from epidemiology, claims, research, and expert input, they decide which barriers the brand must address, which HCPs to target, and whether unbranded education is needed.
A launch plan is only as good as its understanding of the disease. Teams that skip this work end up targeting the obvious specialists while most eligible patients sit undiagnosed in primary care. Disease-state insights are how you find where the real barriers are.
The five questions
- How many patients are there, and where? Prevalence, incidence, and geography.
- How do patients move from symptoms to treatment? And where do they drop off?
- Who diagnoses and who treats? Often different HCPs.
- What do patients get today? Treatment patterns, switching, and discontinuation.
- Why? The beliefs, systems, and costs behind each pattern.
Data sources
| Question | Main sources |
|---|---|
| Size | Published epidemiology, registries, claims |
| Journey | Claims and EHR analysis, patient research |
| HCP landscape | NPI and claims, affiliation data |
| Treatment patterns | Claims, prescription data |
| Why | HCP and patient interviews, surveys, advocacy groups |
Use de-identified data and follow privacy rules. HHS guidance describes de-identification methods.
Finding the diagnosis gap
Many conditions are underdiagnosed. A common analysis compares expected prevalence with diagnosed patients in claims. A large gap suggests:
- Disease awareness for patients.
- Education for primary care on recognizing symptoms.
- Testing support where diagnosis depends on a test. See biomarker testing gaps.
Be careful with the numbers. Claims undercount patients who are diagnosed but not coded, and epidemiology estimates vary.
Mapping the HCP landscape
Claims show which HCPs see patients with the condition and at what stage. Typical findings:
- Primary care sees patients early but refers late.
- A small number of specialists treat most severe patients.
- Referral centers concentrate rare-disease patients.
These findings drive target lists and tiering. See building an NPI target list.
Treatment patterns
Look at first-line choices, time to switch, discontinuation, and combination use. Ask why patients discontinue. Side effects, cost, and lack of benefit need different responses.
Turning insights into plans
For each major barrier, write:
- The evidence that it exists and how big it is.
- Who can fix it: patients, which HCPs, payers.
- What the brand could do before and after launch.
- How you would measure progress.
This becomes the barrier section of the marketing plan.
Common mistakes
- Relying on one data source.
- Treating a modeled diagnosis gap as precise.
- Focusing only on specialists.
- Skipping qualitative work, so you know what happens but not why.
Practical takeaway
Write the patient journey for your condition as five or six steps with an estimated share of patients lost at each. The step with the biggest loss that your brand can influence is where pre-launch education and early launch media should focus.
Frequently asked questions
What are disease-state insights?
Evidence-based understanding of a condition's epidemiology, patient journey, diagnosis, treatment patterns, and the HCPs involved, used to plan commercial strategy.
Where does disease-state data come from?
Published epidemiology, de-identified claims and EHR data, patient and HCP research, advisory input from experts, and patient advocacy groups.
How are disease-state insights used in media planning?
They decide which HCPs and patient segments to reach, which barriers to address, and whether unbranded disease education is needed before or alongside branded media.
Sources
- FDA, Rare Diseases at FDA
- National Cancer Institute, Biomarker Testing for Cancer Treatment
- HHS, Guidance Regarding Methods for De-identification of PHI
External guidance and platform documentation change. Links were current at publication; check them again before relying on them for a decision.
Editorial note. Analysis and frameworks are the author's own and do not represent Acxiom or any current or former employer, client, or named platform. Examples labeled hypothetical or illustrative are not results from real campaigns. Nothing here is legal, regulatory, or medical advice.
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