Ep. 32: When Good Data Leads to Bad Decisions

“Let the data drive the decision” sounds objective. But data doesn’t make decisions. People do. In Episode 32 of Viral Healthcare, Bruce Spurlock, M.D., examines how perfectly accurate data can still lead healthcare leaders toward the wrong conclusion. From dashboards and proxy measures to selection bias and confirmation bias, Bruce explores the assumptions hiding behind the numbers—and why more information doesn’t necessarily create better understanding. He also looks at why a red metric may be a signal rather than a diagnosis, why improving a process measure doesn’t always improve the outcome that actually matters, and why frontline experience can reveal what a dashboard misses. The goal isn’t less data. It’s better judgment. In this episode: Why data is not the same as objectivity How dashboards simplify—and sometimes distort—complexity Process measures vs. outcomes The danger of proxy measures Selection bias and who gets left out of the data How confirmation bias shapes data interpretation Why more metrics can create false confidence How leaders can triangulate quantitative data with frontline experience The questions to ask when someone says, “The data is clear” Hosted on Acast. See acast.com/privacy for more information.