Health Economics and Outcomes Research

Chloe: Welcome to the London School of Business and Administration podcast—where breakthrough ideas meet real-world impact. I'm Chloe, and today we're diving into Health Economics and Outcomes Research—the one concept that quietly shapes everything from boardroom decisions to your daily workflow. Chloe: Have you ever wondered why a life‑saving drug can cost ten times more in one country than another, even when the science is identical? Rohan: That's the heart of health economics, Chloe. It’s the invisible engine that decides how resources flow, balancing clinical benefit, budget impact, and societal value. Historically, we started with simple cost‑minimisation studies in the 1970s, but today we’re talking sophisticated models that incorporate quality‑adjusted life years, real‑world evidence, and patient‑reported outcomes. Imani: I actually saw this play out last quarter when our team was negotiating price for a new oncology therapy in a middle‑income market. The clinical data looked great, but the payers were stuck on the incremental cost‑effectiveness ratio. Chloe: That sounds intense. Rohan, can you break down what an incremental cost‑effectiveness ratio really tells a decision‑maker? Rohan: Absolutely. Think of it as the extra cost you pay for each additional unit of health benefit—usually a QALY. If the ratio falls below a country’s willingness‑to‑pay threshold, the therapy is deemed “good value.” But thresholds differ wildly: the UK uses around £20,000–£30,000 per QALY, while some Asian markets operate on a per‑GDP‑per‑capita rule. Imani: In our case, we initially presented the raw cost per QALY, and the payer rejected it outright. I learned the hard way that numbers alone don’t move the needle; you need to frame the story around budget impact, disease burden, and even equity considerations. Chloe: So the narrative matters as much as the math. What did you change in the presentation? Imani: We built a budget impact model showing the total spend over five years, layered it with a scenario analysis that highlighted potential cost offsets from avoided hospitalisations, and added a patient‑voice video to illustrate real‑world outcomes. Suddenly the conversation shifted from “can we afford it?” to “what happens if we don’t?” Rohan: That’s a textbook example of integrating outcomes research into market access. The framework I teach includes three pillars: clinical efficacy, economic evaluation, and stakeholder engagement. Each pillar informs the next. By quantifying the downstream savings, you turn a cost into an investment. Chloe: It sounds like a delicate dance. What are some common pitfalls you see organisations fall into? Imani: One big mistake is relying on trial data alone without adjusting for real‑world adherence. We assumed 100 % adherence in our model, and the payer called us out on it. The revised model, which accounted for a 70 % adherence rate, actually lowered the cost per QALY because the drug was used less intensively. Rohan: Exactly. Over‑optimistic assumptions inflate both costs and benefits, eroding credibility. Another trap is ignoring the perspective—whether you’re looking from the payer, the hospital, or the societal angle. Each perspective has its own cost components and outcome weights. Chloe: That’s a great reminder. If a listener is just starting out in health economics, what’s a practical first step they can take? Rohan: Start by mastering the basics of decision‑analytic modelling—tree diagrams, Markov models, and sensitivity analysis. There are open‑source tools like TreeAge and R packages that let you experiment without huge budgets. Imani: And pair that with a real‑world case study. I took a published cost‑effectiveness paper, re‑run the model with local cost inputs, and presented it to my manager. It sparked a conversation that led to a pilot reimbursement proposal. Hands‑on practice beats theory alone. Chloe: I love that actionable advice. Before we wrap, what’s one insight you both want our listeners to walk away with? Imani: Health economics isn’t just a spreadsheet; it’s a communication tool that can change patient access. Use the data to tell a compelling story. Rohan: And remember, the field is evolving. Emerging data sources—digital health wearables, real‑world registries—are reshaping outcomes research. Stay curious, stay critical, and keep integrating new evidence into your models. Chloe: Brilliant. Thank you, Rohan and Imani, for sharing your expertise and real‑world wisdom. If this resonated, share it with one person who needs to hear it—and hit subscribe so you never miss an episode that moves you forward. Until next time, keep turning data into impact.