Modernizing the Medical Practice Without Chasing the Next Shiny Tool, with BPM's Caila Cohen, Josh Schmidt, and Sven Jost

On this episode of the MGMA Insights Podcast, host and senior editor Daniel Williams sits down with BPM partners Caila Cohen, Josh Schmidt and Sven Jost to explore what meaningful back-office modernization looks like in healthcare. Their conversation covers technology strategy, cybersecurity, data analytics and automation, with an emphasis on solving clearly defined business problems rather than purchasing technology first.

Episode takeaways

Modernization is not synonymous with buying new technology. As practices add locations, providers and services, they often accumulate disconnected systems, duplicate data entry, manual workarounds and critical knowledge that lives only in employees’ heads.Design around the organization’s current and future needs. Practice leaders should consider how they would build their operations if starting today, then work toward a back office that can scale securely and generate useful, trustworthy information.Start with the business problem, not the product. Before evaluating software, identify what should become faster, easier or more visible. Otherwise, an organization may simply automate a broken process and make the underlying problem harder to correct.Treat cybersecurity as an operational risk. Josh points to unsupported systems, known vulnerabilities, remote-access tools, patient portals and cloud infrastructure as important parts of a practice’s attack surface. Layered defenses and a tested incident-response plan are more dependable than any promised all-in-one solution.Look beyond direct vendors. A practice’s risk extends to the processors, subprocessors and other downstream organizations used by its technology partners. Security due diligence should therefore address fourth-party dependencies, not just the vendor named in the contract.Put guardrails around shadow AI. Employees may use personal or unapproved accounts to enter organizational information into AI platforms, bypassing established controls. Practices need clear acceptable-use rules, approved tools and workforce education appropriate for protected health information and other sensitive data.Turn data into decisions rather than more dashboards. A useful analytics program should help leaders answer three practical questions: What changed? Why did it change? What action should we take next? Shared metric definitions and named data owners help prevent departments from debating conflicting versions of the same number.Begin with one high-value source of friction. R