Why Yesterday’s Methods are Today’s Brain Damage in Post-Acute Care and How AI Becomes Infrastructure You have seen the new wave of “AI assistants” for healthcare: a friendly avatar, smooth chat, and a demo where answers appear as fast as you can type. When you ask whether it will handle your “unique workflows,” the answer is always, “Absolutely—we sit on top of anything.” If you have signed the contracts and lived through the fallout, you have the scars. This is not a use

How legacy EMRs in post-acute care turn small documentation issues into big operational problems In post‑acute care, incumbent EMRs, designed to transition paper records to electronic records, have actually become drivers of missed KPIs, churn, and margin compression. For reasons of data redundancy, lack of coherent workflows and poor fidelity to real-world processes, they function as Error‑Magnifying Records, turning tiny defects at the point of care into outsized business p

Treating AI as an heir to humanity confuses our tools with the people they serve. Ambitious, public claims that “superintelligence” could arrive by 2028 produce concern about job loss or at least reconfiguration. Investments match the ambition, with estimates that training a single frontier model can consume tens of gigawatt hours of electricity—enough to power a major city for days. But we see our field missing a key point: increasing scale and energy use can make systems m